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Related Concept Videos

Relative Motion Analysis using Rotating Axes - Acceleration01:22

Relative Motion Analysis using Rotating Axes - Acceleration

Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame. The absolute velocity of point B is determined by adding the absolute velocity of point A, the relative velocity of point B in the rotating frame, and the effects caused by the angular velocity within the rotating frame.
Time differentiation is...
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the drone...
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it instrumental in...
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the time...
Curvilinear Motion: Polar Coordinates01:27

Curvilinear Motion: Polar Coordinates

In polar coordinates, the motion of a particle follows a curvilinear path. The radial coordinate symbolized as 'r,' extends outward from a fixed origin to the particle, while the angular coordinate, 'θ,' measured in radians, represents the counterclockwise angle between a fixed reference line and the radial line connecting the origin to the particle.
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Related Experiment Video

Updated: May 10, 2026

An Experimental Protocol for Assessing the Performance of New Ultrasound Probes Based on CMUT Technology in Application to Brain Imaging
16:01

An Experimental Protocol for Assessing the Performance of New Ultrasound Probes Based on CMUT Technology in Application to Brain Imaging

Published on: September 24, 2017

CUDA accelerated method for motion correction in MR PROPELLER imaging.

Chaolu Feng1, Jingzhu Yang, Dazhe Zhao

  • 1School of Information Science and Engineering, Northeastern University, Shenyang, CO 110819, China; Key Laboratory of Medical Image Computing of Ministry of Education, Northeastern University, Shenyang, CO 110819, China.

Magnetic Resonance Imaging
|June 8, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a CUDA accelerated method to significantly speed up motion correction in PROPELLER MRI scans. The new technique achieves a 6.5x speedup with minimal impact on image quality, meeting clinical requirements.

Keywords:
ArtifactCUDAMotion correctionPROPELLER

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Medical Imaging
  • Computational Science

Background:

  • PROPELLER MRI collects data in k-space strips, susceptible to artifacts from physiological and physical motion.
  • Existing motion correction algorithms (phase, rotation, translation) have high time complexities, limiting their clinical application.
  • Efficient motion correction is crucial for high-quality MRI image reconstruction.

Purpose of the Study:

  • To develop and evaluate a CUDA accelerated method for motion correction in PROPELLER MRI.
  • To improve the performance of phase, rotation, and translation correction algorithms.
  • To assess the impact of acceleration on image quality and clinical applicability.

Main Methods:

  • Implementation of a CUDA accelerated algorithm on a general PC with a Geforce 8800GT GPU.
  • Application of accelerated phase, rotation, and translation correction techniques.
  • Comparison of accelerated results with non-accelerated implementations.

Main Results:

  • CUDA accelerated phase correction yielded identical results to the non-accelerated version.
  • Accelerated rotation and translation correction showed only minor differences compared to non-accelerated methods.
  • Images reconstructed using the accelerated motion correction met clinical requirements.
  • A speedup ratio of approximately 6.5 was achieved.

Conclusions:

  • The proposed CUDA accelerated method effectively reduces motion artifacts in PROPELLER MRI.
  • The technique offers significant speed improvements without compromising image quality or clinical validity.
  • This approach has the potential for direct application on modern GPUs, enabling greater speedups.